Content authority ranking using browsing behavior

ABSTRACT

An intermediary system operates as an intermediary between content servers and user devices, and provides services for determining page authority based on user browsing behavior. One such service involves receiving user browsing behavior from at least one browser on a user device and using the browsing behavior to assign an authority ranking to a content page (e.g., web page). The intermediary system can determine the content page authority based on explicit user authority rankings and/or implicit authority indications in page traffic data.

BACKGROUND

Page authority represents the relevance of content, e.g. information andlinks, within pages to one another, and domain authority represents thereliability of the domain and relevance of the domain to a topic, forexample a search keyword. Conventionally, authority rankings for pagesand domains are based on the link structure of a network (e.g., theInternet). For example, authority values for a page might be determinedbased on the quantity and quality of other pages and domains thatinclude links to that page. In many cases, however, these authoritymeasures do not accurately reflect users' perceptions.

BRIEF DESCRIPTION OF DRAWINGS

Throughout the drawings, reference numbers may be re-used to indicatecorrespondence between referenced elements. The drawings are provided toillustrate example embodiments described herein and are not intended tolimit the scope of the disclosure.

FIG. 1 illustrates a content delivery environment with an intermediarysystem that determines authority rankings according to one embodiment.

FIG. 2 illustrates example data flows and interactions between a userdevice and intermediary system during determination of authorityrankings according to some embodiments.

FIGS. 3A-3D illustrate various examples of authority associationmappings and corresponding authority rankings.

FIG. 4 illustrates an embodiment of an authority determination techniqueas implemented by an intermediary system.

FIG. 5 illustrates an embodiment of a content to authority associationmap generation technique that can be used with the authoritydetermination techniques described herein.

DETAILED DESCRIPTION Introduction

Aspects of the present disclosure relate to systems and techniques forusing user behavioral data, for example browsing history data includingtraffic data, user-provided authority feedback, and/or content sharingdata, to determine page and/or domain authority. One embodiment involvesan architecture in which the functions of a network content browsingsystem (e.g., a “web browser” application) are distributed among abrowser component running on a server and a browser component running ona user device. The server-based browser component can interact with anumber of browser components running on user devices, for example toretrieve and render content (e.g., web pages), and generate, fordelivery to a user device, a representation of the content that can beutilized by the user device to display a visual representation of thecontent. One or both of the server-based browser and the client browsercan track and store browsing history data for use in determining pageand/or domain authority. In this configuration, the server-based browsercomponent may be referred to as a “headless browser,” and the browsercomponent running at the user device may be referred to as a “clientbrowser.”

Conventional browser applications executing on a user device typicallystore certain types of data relating to a user's browsing behavior,referred to as a browsing history. Browsing history can include a listof content pages (e.g., web pages) and content sites (e.g., domains orweb sites) a user has visited recently, together with associated datasuch as page title, time, and duration of visit, and can be recorded bythe browser for a predetermined period of time in order to provide theuser with a history list and back/forward navigation options. However,the stored data represents the browsing history of just a single user orgroup of users who have access to the computing device storing thebrowser application, and not the aggregate browsing histories of largenumbers of users. Further, by default this browsing history data istypically not shared, but stored only locally on the user device.

As an alternative to implementing the browser fully on the user device,an intermediary system or system, for example a headless browserimplemented on a remote server or other device, can be used to retrieveand format content requested by a client browser as described above. Insome embodiments, the intermediary system can receive data from theclient browser representing some or all of the browsing history for usein determining authority rankings for content pages and content sites.In other embodiments, the intermediary system can track the user'sbrowsing behavior since it processes some or all of the page requestsfrom the user device. In some embodiments, the intermediary system maytrack some browsing behavior and receive some browsing behavior from theuser device (for example, when the browser running on the user deviceretrieves pages directly without going through the intermediary system)so that the intermediary system obtains a complete record of thebrowsing history data. The browsing history data can include trafficdata, for example a number of visits to a specific content page, as wellas content sharing data (e.g., sharing a content page via social media,for example using a feature built in to the client browser) anduser-provided authority feedback data. The traffic data (e.g., number ofvisits to a page or domain) can be used as an implicit indication ofauthority, where greater traffic indicates greater authority. Trafficdata can be temporal in some embodiments, for example tracking trafficover time order to determine trends in authority or limiting trafficdata to the past hours, days, weeks or other time period in order todetermine recent authority.

Authority feedback data and content sharing data can be used as explicitindications of the authority of a page or domain. The authority feedbackdata may be provided by the user for a specific page or domain, forexample using a feature built into the client browser, and can indicatea level of authority the user would assign to the page. To illustrate,the client browser can include a user interface having functionality fora user to provide authority feedback, for example a binary rating (e.g.,authoritative/not authoritative, thumbs up/thumbs down), numericalrating (e.g., from 1 to 10), or scale rating (e.g., one to five stars)regarding the user-perceived authority of a particular page that theuser is visiting. In some embodiments, the authority feedback userinterface can be presented to all users for all content pages. In someembodiments, the authority feedback user interface can be presented onlyto some users, for instance users who are classified as experts or userswho have visited greater than a threshold number of pages. In someembodiments, the authority feedback user interface can be presented onlyfor some pages, for example pages associated with the same category asan expert user. The authority feedback user interface may beincorporated into a browser toolbar in some embodiments. The clientbrowser may also support content sharing on social media, for examplethrough sharing functionality built into the browser, and datarepresenting shared content can be used as an explicit authorityindication.

In some embodiments, the expert or reputation statuses of users can bemeasured based on the content they have posted, and/or user ratings ofsuch content. For example, a user who frequently posts customer reviewsof electronic items in an electronic commerce system may be consideredan expert on electronics, especially if others' ratings of such reviewsare favorable. Examples of methods that can be used to measure thereputations of users based on review activities are described in U.S.Pat. No. 7,664,669, the disclosure of which is hereby incorporated byreference.

The intermediary system may store this data anonymously, and mayaggregate the browsing history data for a global group of all usersand/or categories of users. Global traffic data can provide theintermediary system with implicit authority indications regarding siteor domain popularity. User feedback can provide the intermediary systemwith explicit authority indications regarding site or domainreliability, relevance, or quality. The implicit and explicit authorityindications can be associated with specific pages or domains in acontent-to-authority association mapping generated by the intermediarysystem. The intermediary system can then use the authority indicationsassociated with a page or domain to determine an authority of the pageor domain.

In one example, the intermediate system can determine a global authorityfor a page or domain based on one or both of global traffic data andaggregate user feedback. In another example, the intermediate system candetermine a categorical authority for a page or domain based on trafficdata and/or user feedback among a particular category of users. Forexample, based on user-provided information or analysis of userbehavior, the client browser or intermediary system can classify a useras an “expert” in one or more categories. To illustrate, theintermediary system may categorize a user as an expert in cooking/bakingbased on one or more of frequent visitation to recipe-related web sites,membership or posts in cooking forums, and purchase history fromelectronic commerce systems including cooking-related items. A user maybe generally categorized as an expert based on factors including higherthan average browsing time or page visit numbers and providing more thana threshold amount of feedback regarding page authority. Expert userscan be considered authoritative regarding quality pages withincategories associated with the user, and the intermediary system maygive more weight to authority indications from such users. Categoricalauthority of pages can provide information about relevance of a page toa particular type of user. User categories can be based on perceiveduser interest, user device type, user geographic or demographicinformation, browsing time, and the like. In some embodiments, one orboth of global authority and categorical authority may be based onbrowsing history data from users outside of the category with authorityindications from expert users weighted more heavily than authorityindications from other users.

In some examples a complete browsing history can be sent from the clientdevice to the intermediary system, and in other examples the clientbrowser can extract implicit and explicit authority indications orperform content to authority association mappings based on the userbrowsing history and send the extracted indications or associationmappings to the intermediary system. The amount or type of data based onbrowsing history that is shared with the intermediary system may beuser-specified.

In various embodiments, the intermediary system can use various aspectsof explicit and/or implicit authority indications present in browsinghistory data in authority determinations. For example, page or domaintraffic can be used to determine authority based on popularity, wherehigher traffic to a page or domain indicates higher authority. Thebrowsing history data can provide temporal trends in authority, forexample authority at different times of day, different seasons, and thelike, as well as changes in authority over time. In some examples, theduration of a visit to a page and/or the patterns of usage can impactthe authority value determined for the page based on that information,for example whether a user came to the page via a referrer, link click,search engine etc. Social signals can also provide implicit authorityindications; for example a domain or page that is heavily shared onsocial media can be assigned a higher authority ranking than a domain orpage that is infrequently shared. Authority can be determined inassociation with device type, for example in order to provide relativeauthority of a page or domain in mobile device traffic versus trafficfrom desktop browsers. In some embodiments, the “active and used” linkedstructure of the network can be taken into account when determiningauthority. For example, if many active links refer to a page and theactive links are frequently followed by users, this would provide ahigher authority ranking as opposed to relatively stale links that arenot used frequently. Categorical authority can be language and/orlocation based in order to provide data regarding geographic trends inauthority. Authority can also be based at least partly on determiningthat a page or domain satisfies an information need of a user, forinstance by figuring out a browsing session information need throughuser profile modeling and determining that a particular (e.g., last orlongest-visited) page satisfied the information need. The intermediarysystem can determine that the information need is associated with atopic or category, and the authority of the page that satisfied theinformation need can be increased in that category. The intermediarysystem can calculate authority based on a weighted combination ofvarious dimensions and can learn and tune weights dynamically based onweb traffic and explicit user feedback.

In some implementations, use of categorical authority for certaincontent sites can generate a high authority ranking for the content sitewhich would, based solely on general traffic data, receive a lowerauthority ranking. For example, a particular page or domain thatprovides expertise on coffee-related items may have a low overalltraffic volume, however a large percentage of the sites visitors may be“coffee expert” users. The level of expertise of a user on the topic ofcoffee can be determined, in some examples, based on the user browsing anumber of content sites relating to coffee and associated items (e.g.,espresso or cappuccino machines, coffee bean growing books or supplies,coffee bean roasting supplies, and the like), on the user purchasingcoffee or associated items from an electronic catalog, and/or on theuser submitting content (e.g., creating coffee item reviews, contentsites, or coffee forum submissions) relating to coffee or associateditems. Accordingly, if a threshold level of users visiting theparticular page or domain that provides expertise on coffee-relateditems are determined to have high expert scores on the topic of“coffee,” then the categorical authority ranking for that page or domainin the category of coffee can be high, even if the overall authorityranking is lower due to low traffic volume.

Being able to detect high-quality content across potentially millions ofcontent pages and content sites can enable an intermediary system (orother type of system) to provide beneficial features for users. Forexample, categorical page and domain authority information can be usedto present personalized information to a user. To illustrate, theintermediary system may analyze information associated with the user(e.g., browsing history data, purchase history data, user profile data,and the like) and associate the user with one or more categories. Theintermediary system can determine that a page or domain is highlyauthoritative in the categories and present the page or domain to theuser as a recommended site. An intermediary system can also leveragepage and/or domain authority for advertisements in some embodiments. Forexample, pages with high authority rankings in a particular category canbe recommended in advertisements to users determined to be associatedwith the category.

An intermediary system can also leverage page and/or domain authorityfor other monetization avenues, for example exposing the authorityranking and content analysis of a content page as a service in order toassist users (e.g., creators and/or managers of the pages and domains)in increasing the quality of their content to increase their authorityranking. Users may wish to improve the authority of their pages ordomains in order to gain a competitive advantage, receive greatertraffic, and thereby increase their sales and/or advertising revenue.Accordingly, the intermediary system may provide a service portal forpresenting general information and tips to site owners for improvingauthority (e.g., update content regularly, involve social media forcontent sharing). The service portal may also provide detailed analyticsof performance based on the authority association mappings (e.g., yourpage is popular among “expert” users interested in science, your page ispopular among laptop users but unpopular among tablet users, etc.) toassist site owners in improving their content. The service portal can beused to present users with information pertaining to any of theassociations based on implicit or explicit authority indicationsdescribed herein, and may present users with a visual representation ofpage authority over time.

An intermediary system can also leverage page and/or domain authorityfor improving user experience, for example by providing a presentationmodification service to modify presentation of content of pages ordomains having low categorical authority rankings on a specific type ofdevice so that the content is more suitably displayed on the device. Toillustrate, the presentation modification service may identify a pagewith a high global authority ranking but a low mobile device authorityranking as a candidate for modifying presentation of content deliveredto users requesting the content from mobile devices. The presentationmodification service can retrieve the content, determine an originalpresentation structure as indicated in the document object model of thecontent page, determine a modified presentation structure based on knownmobile device presentation preferences (e.g., presenting smallerportions of content per page than in a laptop browser, providing videocontent in mobile-compatible formats, delivering content using methodsto compensate for slower network connection speeds, and the like), anddeliver the content in the modified presentation structure to a userrequesting the content from a mobile device.

Although aspects of the embodiments described in the disclosure willfocus, for the purpose of illustration, on a distributed browsing systemwith separate server-based and client-based browser components designedspecifically to work in conjunction with one another (e.g., a headlessbrowser instance running on a server and a corresponding client browserinstance running on a user device), one skilled in the art willappreciate that the techniques disclosed herein may be applied to anynumber of services, processes, or applications. For example, thedisclosed process may be implemented by a non-intermediary server systemthat analyzes behavioral data reported by browsers/user devices. In someembodiments, an existing browser application that runs on a user devicemay be configured to determine page authority rankings. For example, abrowser add-in or extension may be installed on a user device tofacilitate one or more of communicating with a headless browser or otherservice, retrieving browsing history data from one or more users,generating page to authority indication association mappings, andranking pages based on the mapping information.

The authority determination techniques described are herein withreference to content pages and content sites. As used herein, the term“content item” can refer to any content page (for example, a web page)or any content site (for example, a web site or domain).

Various aspects of the disclosure will now be described with regard tocertain examples and embodiments, which are intended to illustrate butnot limit the disclosure.

System Components

FIG. 1 illustrates an example network environment in which features canbe implemented for processing content pages on an intermediary systemand generating authority rankings. The network environment shown in FIG.1 includes various user devices 102, an intermediary system 104, andvarious content sources, including origin content servers 106 andcontent delivery network (“CDN”) servers 108. The system components maycommunicate with each other via one or more communication networks 110in order to deliver content pages hosted on CDN servers 108 and/ororigin servers 106 to user devices 102 via intermediary system 104. Theintermediary system maintains browsing history data in association withthe user devices 102 for use in determining page and domain authority.The network 110 may be a publicly accessible network of linked networks,possibly operated by various distinct parties, such as the Internet. Inother embodiments, the network 110 may include a private network,personal area network, local area network, wide area network, cablenetwork, satellite network, cellular telephone network, etc. orcombination thereof, each with access to and/or from the Internet.

As will be appreciated by those of skill in the relevant art, thenetwork environment may include any number of distinct user devices 102and/or content sources 106, 108. In addition, multiple (e.g., two ormore) intermediary systems 104 may be used. For example, separateintermediary systems 104 may be located so that they are close (ineither a geographical or networking sense) to groups of current orpotential user devices 102 or content sources 106, 108. In such aconfiguration, a user device 102 may request content via theintermediary system 104 to which it is closest, rather than all userdevices 102 requesting content via a single intermediary system 104.Further, as mentioned above, the system that analyzes the browsingbehaviors and generates authority measures need not operate as anintermediary.

The user devices 102 can include a wide variety of computing devices,including personal computing devices, terminal computing devices, laptopcomputing devices, tablet computing devices, electronic reader devices,mobile devices (e.g., mobile phones, media players, handheld gamingdevices, etc.), wearable devices with network access and programexecution capabilities (e.g., “smart watches” or “smart eyewear”),wireless devices, set-top boxes, gaming consoles, entertainment systems,televisions with network access and program execution capabilities(e.g., “smart TVs”), and various other electronic devices andappliances. Individual user devices 102 may execute a browserapplication 120 to communicate via the network 110 with other computingsystems, such as the intermediary system 104 or content sources 106 and108, in order to request and display content.

Illustratively, a user may use a browser application 120 to requestnetwork-accessible content (e.g., content pages, images, video, etc.)hosted or provided by a content source, such as an origin content server106 or a CDN server 108. The user device 102 or browser application 120may be associated with the intermediary system 104 or otherwiseconfigured to request the content through, and receive content from, theintermediary system 104 rather than communicating directly with thecontent source. The browser application 120 may include browsing datastorage 121 that stores browsing history data representing userinteractions with content provided to the browser application 120. Insome embodiments, the browser 120 may be a conventional web browser thatis not specifically designed or configured to store or analyze browsingdata pertaining to page or domain authority. In some embodiments,browser 120 can be provided with modules that store and communicateinformation relating to authority determinations, as discussed in moredetail with respect to FIG. 2.

The intermediary system 104 can be a computing system configured toretrieve content on behalf of user devices 102 and send the content tothe user devices 102. For example, the intermediary system 104 can be aserver or group of servers that may be accessed via the network 110. Insome embodiments, the intermediary system 104 may be a proxy server, asystem operated by an internet service provider (ISP), and/or some otherdevice or group of devices that retrieve content on behalf of userdevices 102.

The intermediary system 104 may include various modules, components,data stores, and the like to provide content retrieval and the authoritydetermination and ranking functionality described herein. For example,the intermediary system 104 may include a server-based browserapplication or some other content rendering application to processcontent retrieved from content sources. Such a content renderingapplication may be referred to as a “headless browser” 140. Generallydescribed, a headless browser 140 does not (or is not required to) causedisplay of content by a graphical display device of the server on whichthe headless browser 140 is executing. Instead, the headless browser 140provides representations of the content to separate user devices 102that enable the user devices 102 to cause display of the content.Illustratively, the headless browser 140 may obtain requested contentfrom an origin content server 106 and/or CDN server 108, obtainadditional items (e.g., images and executable code files) referenced bythe requested content, execute code (e.g., JavaScript) that may beincluded in or referenced by the content, generate a representation ofthe content usable to display a graphical representation of the content,and transmit the representation to the user device 102. By performingsome or all of these operations at the intermediary system 104, thesubstantial computing resources and high-speed network connectionstypically available to network-based server systems may be leveraged toperform the operations much more quickly than would otherwise bepossible on a user device 102 with comparatively limited processingcapability. In addition, by providing content page representations to alarge number of the user devices 102 and communicating with the userdevices 102 over a network, the intermediary system 104 may be able toobtain browsing history data representing visits to and interactionswith a large number of content pages and content sites by a large numberof users.

The intermediary system 104 may include various modules to provide theauthority determination functionality described above and in greaterdetail below. For example, the intermediary system 104 may include anauthority association map builder 150, an authority ranking module 160,an authority utilization module 170, and data repositories for loggeduser behaviors 144 and content authority 180. The functionalities of andcommunications between these components is described in more detail withrespect to FIG. 2.

As an example, the headless browser may be implemented using the opensource Chromium™ browser, with appropriate modifications to implementauthority determination the other features described herein. In someembodiments, Chromium™ code may be modified to request and/or receivebrowsing history data from a number of computing devices of users,analyze the browsing history data, build an authority association map,and determine authority rankings of a number of content pages and/orcontent sites. Chromium™ code may also be modified to perform thevarious authority utilization techniques described herein, for exampleadvertising content pages or content sites to specific users, providinga service portal for assisting users with increasing authority rankingsof their content pages or content sites, and providing a content displaymodification service to address content display issues evidenced bycategorical authority rankings. In other embodiments, a headless browsercomponent can be developed specifically to implement the authoritydetermination and utilization techniques described herein.

The intermediary system 104 may include additional modules, components,data stores, and the like to provide the features described above and ingreater detail below. For example, the intermediary system 104 mayinclude a cache 142 that stores content items received form contentsources 106 and 108 and the like. The intermediary system 104 may alsoinclude a logged “user behaviors” data store 144 that stores informationabout user requests and interactions with content as well as browsingdata received from user devices.

The intermediary system 104 may be a single computing device, or it mayinclude multiple distinct computing devices, such as computer servers,logically or physically grouped together to collectively operate as anintermediary system. The components of the intermediary system 104 caneach be implemented as hardware, such as a server computing device, oras a combination of hardware and software. In addition, the modules andcomponents of the intermediary system 104 can be combined on one servercomputing device or separated individually or into groups on severalserver computing devices. In some embodiments, the intermediary system104 may include additional or fewer components than illustrated in FIG.1.

In some embodiments, the features and services provided by theintermediary system 104 may be implemented as web services consumablevia the communication network 110. In further embodiments, theintermediary system 104 is provided by one more virtual machinesimplemented in a hosted computing environment. The hosted computingenvironment may include one or more rapidly provisioned and releasedcomputing resources, which computing resources may include computing,networking and/or storage devices. A hosted computing environment mayalso be referred to as a cloud computing environment.

The origin content servers 106 and CDN servers 108 can correspond tological associations of one or more computing devices for hostingcontent and servicing requests for the hosted content over the network110. For example, a content server 106 or CDN server 108 can include aweb server component corresponding to one or more server computingdevices for obtaining and processing requests for content (such ascontent pages) from user devices 102, the intermediary system 104, orother devices or service providers. In some embodiments, one or morecontent servers 106 may be associated one or more CDN service providers(e.g., entities that manage multiple CDN servers 108), applicationservice providers, etc.

Although in the examples described herein the intermediary system 104 isconfigured to communicate with user devices 102 to receive traffic data,in some embodiments the origin content servers 106 and/or CDN servers108 can be configured to store traffic data and send the traffic data tothe intermediary system.

Example Component Communications

FIG. 2 illustrates example data flows and interactions between a userdevice and intermediary system during generation of authoritydeterminations according to some embodiments. Although the illustratedcommunications involve the user device 102 and intermediary system 104of FIG. 1, similar communications can take place between any clientdevice and intermediary system capable of executing the authoritydetermination techniques described herein.

Browser 120 of the user device 102 can include a browsing datarepository 122 for storage of browsing history data. Browsing historycan include a list of content pages (e.g., web pages) and content sites(e.g., domains or web sites) a user has visited recently together withassociated data such as page title, duration of visit, time of visit,and timing and/or location of user zooming and scrolling within thepage, and can be recorded by the browser 120 for a predetermined periodof time in order to provide the user with a history list andback/forward navigation options.

Browser 120 can also include content sharing module 121 configured toprovide a user interface having functionality for the user to sharecontent pages on social media. For instance, the content sharing module121 can provide an interface as part of a browser toolbar that allows auser to share, using the browser 120, a portion or all of a currentlyviewed content page using one or more social media accounts belonging tothe user. The content sharing module 121 can be configured to store datarepresenting user sharing of content on social media with the browsinghistory data in data repository 122.

Browser 120 can also include content rating module 123 configured toprovide a user interface having functionality for the user to provideauthority feedback representing user-perceived authority of contentpages on social media. To illustrate, the content rating module 123 canprovide, for example as part of a browser toolbar, a user interfacehaving functionality for a user to give provide authority feedback. Thefeedback can be provided in the form of a binary rating (e.g.,authoritative/not authoritative, thumbs up/thumbs down), numericalrating (e.g., from 1 to 10), or scale rating (e.g., one to five stars)regarding the user-perceived authority of a particular page that theuser is visiting. The content sharing module 123 can be configured tostore data representing the authority feedback with the browsing historydata in data repository 122. Content rating module 123 can determine ifand when to expose the content rating functionality. For example,content rating module 123 can determine that a user visiting a page isan expert on a topic or category associated with the content page or thecontent site hosting the content page, and based on that determinationthe content rating module 123 can prompt the user to provide a rating ofthe perceived authority of the content page and/or content site relatingto the topic.

As illustrated, the browser 120 of the user device 102 can send browsinghistory data 215 to the logged user behaviors data repository 144 of theintermediary system 104. The browsing history data 215 can include pagevisit data (e.g., traffic data), content sharing data, content ratingdata, and browsing session data. In some embodiments, the browsinghistory data 215 can be accompanied by data representing informationabout user device 102, for example device type, display size, andconfiguration of browser 120, to name a few, as well as datarepresenting information about the user, for example a stored userprofile. The browser 120 can be configured such that browsing historydata 215 is sent to the repository 144 periodically (for example, onceper day, at the conclusion of each browsing session, etc.) or at therequest of the intermediary system 104.

As illustrated in FIG. 1, intermediary system 104 can include headlessbrowser 140. In some embodiments, the intermediary system 104 mayinstantiate the headless browser 140 to interface with the clientbrowser 120 to request or receive browsing history data 215 and routereceived browsing history data 215 to the logged user behaviorsrepository 144. The intermediary system 104 may additionally oralternatively obtain browsing history data by virtue of being anintermediary (e.g., it may log the page requests 205 that it receives inassociation with a device or user ID). Data representing page requestsand responses 205 can be logged by the intermediary system 104 as partof the browsing history data stored in the logged user behaviors datarepository 144.

The authority association map builder 150 can receive the browsinghistory data 215 from the logged user behaviors data repository 144. Forexample, the authority association map builder 150 can be configured toupdate authority associations stored in the content-to-authorityindication association map 190 at periodic intervals as needed forgenerating up-to-date authority rankings for content pages and contentsites. As discussed above, the browsing history data 215 can includetraffic data representing a number of user visits to each of a number ofcontent pages and content sites as well user interactions includingsharing and rating of content pages. User interactions can includevarious behaviors of a user with respect to a content item, for exampleproviding authority feedback (e.g., a rating) representing the user'sperceived authority of the content, sharing of the content or a portionof the content by the user on social media or electronic messagingsystems, and bookmarking the content, to name a few. Some or all ofthese user interactions may be enabled through functionality built intothe browser component on the user device. Authority association mapbuilder 150 can be configured to receive the browsing history data fromthe browser component on the computing devices of a plurality of browserusers; identify, based at least partly on analyzing the traffic data,implicit authority indications for each of the plurality of contentpages; identify, based at least partly on analyzing the userinteractions, explicit authority indications for at least the subset ofthe plurality of content pages; and build an authority association mapassociating each of the plurality of content pages with anycorresponding implicit authority indications and explicit authorityindications.

For example, traffic analysis module 154 can determine the implicitauthority indications by analyzing a number of visits to each contentpage and/or by performing a comparison of number of visits to eachcontent page across a number of content pages. Such page popularity, asdetermined based on traffic data, represents one factor that can be usedto determine authority of a content page or content site. Trafficanalysis module 154 can also partition the traffic data into categories,for example based on geographic location of users, page access time ofusers, page language access of users, and the like, for use indetermining categorical authority indications of content pages andcontent sites.

In some embodiments, weighting module 152 can determine relative weightsfor a number of factors or authority indications used to determineauthority of a content page or content site, for example includingdetermining weights for the implicit authority indication based ontraffic data, explicit authority indications based on content shares orcontent rating, and/or expert user categorical authority indicationsassociated with a page. In certain embodiments, determining user expertauthority weightings can be done offline—that is, separate from and inadvance of the authority ranking processes described herein—andweighting results can be stored for future use.

In some implementations, weighting module 152 can perform variousanalyses of user profile data to ascertain a degree of expertise theuser has in a particular category or a global expertise of the user.Global expertise of a user can be based, for example, on an amount ofbrowsing history data associated with the user, where more browsing datamay indicate a higher level of global expertise, on other users' ratingsor votes relating to content submitted by the user, or on other analysisof a quality of content submitted by the user. Global expertise may beused to assign a relatively higher score or weighting to all authorityindications determined from a user's behavioral data in someimplementations. Some examples of methods that can be used to measurethe level of expertise of users based on purchase activity are describedin U.S. Pat. No. 7,536,322, the disclosure of which is herebyincorporated by reference. Weighting module 152 can additionally oralternatively analyze the browsing history data 215 corresponding toindividual users to determine whether the user is authoritative orexpert in a certain category, such as cooking, technology, or the like,and whether to assign a relatively higher weight to authorityindications stemming from analysis of the browsing history datacorresponding to the user when ranking content pages or content sitesassociated with the category. Categorical weightings can be used toassign a relatively higher score or weighting to authority indicationsfor pages relating to a particular category. The weighting module mayperform such analyses to determine user weighting offline, that is,separately from the authority ranking process, and store the determineduser weightings for later use.

The explicit authority indications, implicit authority indications,categorical authority indications, and corresponding weights for eachcontent page can be sent as association data 230 for storage in thecontent to authority indication association map 190. Examples ofauthority association mappings and corresponding authority rankings arediscussed in more detail below with respect to FIGS. 3A-3D. In someembodiments, association data 230 can also include associations betweenexpert users and categories as well as content pages and the categories.Accordingly, the resulting map data 235 can include both aggregateauthority indications as well as categorical authority indications forcontent pages and content sites, as well as weights for authorityindications.

The map data 235 can be output to the authority ranking module 160 forassigning an authority ranking to each of the content pages and/orcontent sites. The authority ranking module 160 can use the weightedauthority indications in the map data 235 to determine one or both of anaggregate authority ranking and a categorical authority ranking (ormultiple categorical authority rankings) for content pages and/orcontent sites. In some examples, authority can be calculated based on a100-point, logarithmic scale. Thus, it can be easier to increase acontent page authority ranking from 20 to 30 than it would be toincrease the authority ranking from 70 to 80. Other suitable ranking orscoring methods can be used to determine authority based on the weightedmap data 235 in other examples.

The resulting authority rankings can be stored in the content authoritydata repository 180 and updated as different authority rankings arecalculated by the authority ranking module 160. Each content page andcontent site can be stored in association with an aggregated authorityranking 182. Based on availability of explicit indications by expertusers or partitioning of traffic data into categories, some or allcontent pages and content sites may be stored in association with acategorized authority ranking 184.

The authority ranking technique performed by the authority associationmap builder 150 and authority ranking module may be performed “offline”by the intermediary system at periodic or irregular intervals in orderto provide the content authority data repository 180 with current,updated authority rankings. The authority rankings stored in the contentauthority data repository 180 can be accessed in “real time” by theauthority utilization module 170 in response to use of the authorityrankings during user browsing sessions or as a monetized service.Authority utilization module 170 can provide services to the browser 120of the user device based on the authority rankings.

Authority utilization module 170 can include various modules formonetizing or otherwise utilizing the determined authority rankings. Forexample, advertising module 160 can use categorical page and domainauthority information to present personalized information to a userbased on correlating information representing the user with one or morecategories, and determining that a page or domain is highlyauthoritative in the categories. In some examples, advertising module160 can recommend pages with high authority rankings in a particularcategory in advertisements to users determined to be associated with thecategory.

Authority utilization module 170 can also leverage page and/or domainauthority for other monetization avenues. For example, service portal181 can provide a user interface for exposing the authority ranking andcontent analysis of a content page as a service in order to assist users(e.g., creators and/or managers of the pages and domains) in increasingthe quality of their content to increase their authority ranking.Because higher authority rankings may indicate a likelihood of betterplacement in search results, users may wish to improve the authority oftheir pages or domains in order to gain a competitive advantage, receivegreater traffic, and thereby increase their sales and/or advertisingrevenue. Accordingly, the intermediary system 104 may provide a serviceportal 181, for example as an application or content site, forpresenting site owners with general information and tips for improvingauthority (e.g., update content regularly, involve social media forcontent sharing) as well as detailed analytics of performance based onthe authority association mappings (e.g., your page is popular among“expert” users interested in science, your page is popular among laptopusers but unpopular among tablet users, etc.) to assist site owners inimproving their content. The service portal 181 can be used to presentusers with information pertaining to any of the associations andimplicit or explicit authority indications described herein, and maypresent users with a visual representation of authority ranking changesover time.

Authority utilization module 170 can also leverage page and/or domainauthority for improving user experience, for example by providingcontent presentation modification service 152 to modify presentation ofcontent of pages or domains having low categorical authority rankings ona specific type of device so that the content is more suitably displayedon the device. To illustrate, the content presentation modificationservice 152 may identify a page with a high global authority ranking buta low mobile device authority ranking as a candidate for modifyingpresentation of content delivered to users requesting the content frommobile devices. Content presentation modification service 152 canretrieve the content, determine an original presentation structure asindicated in the document object model of the content page, determine amodified presentation structure based on known mobile devicepresentation preferences (e.g., presenting smaller portions of contentper page than in a laptop browser, providing video content inmobile-compatible formats, delivering content using methods tocompensate for slower network connection speeds, and the like), anddeliver the content in the modified presentation structure to a userrequesting the content from a mobile device. Content presentationmodification service 152 can identify other content display problems,for example localization (e.g., foreign language translations) problems,browser type or version display problems, and the like based ondisparities between categorical authority rankings.

Example Content to Authority Association Mappings

FIGS. 3A-3D illustrate various examples of authority associationmappings and corresponding authority rankings. FIG. 3A illustrates anexample of explicit authority associations 305 generated based onuser-provided feedback on perceived page quality. As illustrated, fivecontent pages (listed as A.com, B.org, C.net, D.gov, and E.edu) eachhave a varying number of user scores stored in association with thepage. Each user score is accompanied by a user weight, which can bedetermined based on “expert” status of the user as discussed above, orbased on a relative level of association of the user with one or morecategories assigned to the content page. Based on the user-assignedratings and the user weights, the intermediary system 104 can generate auser-given quality score to store as an explicit indication of theauthority of each of the pages. Though not illustrated, user shares ofthe content can also be factored in to the explicit authorityindications 305.

FIG. 3B illustrates an example of implicit authority associations 310based on traffic data analysis. Each of the five content pages shown inthe explicit authority associations 305 of FIG. 3A is shown again in theimplicit authority associations 310. However, in some examples not allpages associated with implicit authority associations 310 will also beassociated with explicit authority associations 305, based on theavailability of user-generated content rating data and/or contentsharing data. The implicit authority associations 310, represented bythe traffic-based score, are based on a number of factors such as totalvisits to the content page, duration of the existence of the contentpage, average duration of a visit to the content page, and visits withina predetermined timeframe (for example, to increase the score of a pagewith a higher number of recent visits even if the page is relatively newor has less total visits than another site). The intermediary system 104can generate these factors based on analyzing traffic data and assignvarying weights to the factors to generate the traffic-based score.

In some embodiments, user characteristics (e.g., the extent to which agiven user is an expert on a topic or subject associated with the siteor page) may be considered in generating the traffic-based scores. Thismay be accomplished by, for example, giving more weight to visits byexperts, or by determining the fraction of visits that are by experts.In some embodiments, the authority score for a site or page may be anormalized score (e.g., on a scale of 0 to 100) representing the extentto which those who visit the site or page are experts on a topic orsubject associated with the site or page.

To illustrate, the intermediary system 104 can record a number ofaccesses to a content item and can record browsing history data, contentposting, data, or other data of the users who accessed the content item.In one embodiment, the intermediary system 104 can determine a firstportion of the number of accesses by expert users of the plurality ofusers and determine a second portion of the number of accesses bynon-expert users of the plurality of users, and can generate anauthority score for the content item by weighting the first portion ofthe number of accesses by the expert users more heavily than the secondportion of the number of accesses by the non-expert users. In anotherembodiment, the intermediate system 104 can determine an expert scorefor some or all users that accessed the content item, determine a numberof accesses of the content item by each of the users, and generate anauthority score for the content item based at least partly on the expertscore for each user and the number of accesses by each user. Expertscores can reflect different degrees of being an expert in someexamples, for instance by scoring each user in terms of expertness on atopic. The intermediary system 104 can then determine the averageexpertise level of those who visit a given page or site for use incalculating the authority score of the page. Expert scores, expertstatus, and non-expert status may be determined based on analysis of thebrowsing history, content posting, other users' reaction to or rating ofcontent posted by the user (e.g., thumbs up or thumbs down votes of aproduct review written by the user for an item in an electroniccatalog), purchase history, forum or group membership, or otherbehavioral data of the users. Accordingly, traffic-based scores can beweighted more heavily with respect to traffic by expert users or userswith higher expert scores.

FIG. 3C illustrates an example of global authority rankings 315 for eachof the five content pages (A.com, B.org, C.net, D.gov, and E.edu) basedon the explicit authority indications 305 represented by the user-givenquality score and the implicit authority indications 310 represented bythe traffic-based score. As described above, global authority rankings315 can be based on analysis of all implicit and explicit authorityindications associated with a page. The illustrated global authorityranking can be calculated based on a 100-point, logarithmic scale usingthe user-given quality score and the traffic-based score. Thus, it canbe easier to increase a content page authority ranking from 20 to 30than it would be to increase the authority ranking from 70 to 80. Othersuitable ranking or scoring methods can be used to determine authorityin other examples.

FIG. 3D illustrates an example of categorical authority rankings 320 foreach of the five content pages (A.com, B.org, C.net, D.gov, and E.edu).As described above, categorical authority rankings 320 can be based onanalysis of a subset of the implicit and explicit authority indicationsassociated with a page, for example relating to a specific type oftraffic data or a specific type of user. The ranking categoriesillustrated provide some non-limiting examples of categories that can beuseful for categorical authority rankings 320. For example, looking atthe ranking categories associated with E.edu, it is apparent that E.eduhas higher authority among users of personal computers (e.g., desktopand laptop computers) than among mobile device users (e.g., smartphoneusers). This disparity in categorical rankings can be used by theservice portal 161 or content display modification module 162 asdescribed above.

Example Authority Determination Techniques

FIG. 4 illustrates an embodiment of an authority determination technique400 as implemented by an intermediary system. The authoritydetermination technique 400 can be performed by the authorityassociation map builder 150 and authority ranking module 160 ofintermediary system 104 in some embodiments, and may be performed“offline” at periodic or irregular intervals in order to provide currentauthority rankings.

At block 405, the authority association map builder 150 can retrieve,from logged user behaviors data repository 144, browsing history dataincluding traffic data indicating visits by the plurality of browserusers to a plurality of content pages of a plurality of content sitesand user interactions with content of at least a subset of the pluralityof content pages.

At block 500, the authority association map builder 150 can buildcontent to authority association mappings between content page andauthority indications based on retrieved browsing history. As describedabove, such association mappings can include associations betweencontent pages and content sites with implicit authority indicationsbased on global and/or categorized traffic data and explicit authorityindications based on user-provided content ratings and/or contentshares. The association mappings can also include associations betweenspecific users, authority indications provide by browsing history dataof the specific users, page categories, and content pages and contentsites. Further details of the content to authority association mapbuilding are discussed with respect to FIG. 5. In some embodiments,building the content to authority association map can include generatinguser expert scores representing an extent to which particular users areexperts on topics/subjects of the content they have browsed. Asdiscussed above, expert scores may be determined based on analysis ofbehavioral data of a user, for example one or more of the browsinghistory, content posting, other users' reaction to or rating of contentposted by the user (e.g., thumbs up or thumbs down votes of a productreview written by the user for an item in an electronic catalog),purchase history, or forum or group membership, of the user.

At block 410, the ranking module 160 can rank content page authoritybased on the content to authority association mappings. For example, theranking module 160 can use weights associated with a number of factorsas shown in FIGS. 3A-3D to generate a global authority ranking for eachpage and categorical authority rankings for some or all pages.

At block 415, the intermediary system 104 can store the content pageauthority rankings for later use. One use of authority rankings, forexample, involves use in monetization services such as advertising,content service portal provision, and content display modification asdescribed above. Other uses of authority rankings include determinationsregarding what pages to present to a user, for instance in response to akeyword search or other query.

FIG. 5 illustrates an embodiment of a content to authority associationmap generation technique 500 that can be used with the authoritydetermination techniques described herein. The content to authorityassociation map generation technique 500 can be performed by theauthority association map builder 150 of intermediary system 104 in someembodiments, and can be included as block 500 of the authoritydetermination technique 400.

At block 505, the authority association map builder 150 can assign auser of the plurality of users who have contributed to the browsinghistory data to one or more categories based on analysis of the browsingbehavior of the user. For example, if the user has made more than athreshold number of visits to technology-related content pages then theuser can be associated with a category of “technology.” The authorityassociation map builder 150 may associate a user with a category of“cooking/baking” based on the user traffic data indicating more than athreshold number of visits to cooking, baking, or recipe-related websites. Other aspects of the browsing history data can be used toassociate the user with categories in other examples, for instance typesof content pages shared or rated by the user.

At block 510, the authority association map builder 150 can identifyimplicit authority indications in the traffic data of the user'sbrowsing history. The authority association map builder 150 canselectively store only implicit authority indications associated withpages that are also associated with the category or categories of theuser in some embodiments.

At block 515, the authority association map builder 150 can identifyexplicit authority indications in the user browsing history, for examplefrom content sharing or content rating actions that the user has taken.The authority association map builder 150 can selectively store onlyexplicit authority indications associated with pages that are alsoassociated with the category or categories of the user in someembodiments.

At block 525, the weighting module 152 of the authority association mapbuilder 150 can provide a weighting or expert score for the implicitand/or explicit page authority indications extracted from the browsinghistory of a particular user with respect to content pages associatedwith the one or more categories. For example, if the user is determinedto be an expert or to have a high degree of expertise (generally or inthe one or more categories), then the weighting module 152 can assignexpert weighting to implicit and explicit page authority indicationsdetermined from the user's browsing history in association with contentpages that are also associated with the one or more categories. Expertweighting may be a standard high weighting or may be a variable score ona scale of possible scores based on a level of expertise determined forthe user. For example, if the user frequently visits technology-relatedcontent pages, is a member and/or prolific poster withintechnology-related forums, or has a purchase history from an electroniccommerce system indicating interest in technology (for instance byfrequently purchasing books on the topic) then the user can bedetermined as an expert in the category of “technology.” The authorityassociation map builder 150 may determine that the user is an expert inthe category of “cooking/baking” based on one or more of frequentvisitation to recipe-related web sites, membership or posts in cookingforums, and a purchase history from electronic commerce systemsincluding cooking-related items. Accordingly, the authority indicationsgleaned from the browsing behavior of the user can have a greater impacton a categorical authority ranking for the content pages than authorityindications gleaned from the browsing behavior of non-expert users.

In some scenarios, the user may be determined to not be an expert or tohave a low degree of expertise (generally or in the one or morecategories), and the weighting module 152 can assign standard weightingto implicit and explicit page authority indications determined from theuser's browsing history in association with content pages that are alsoassociated with the one or more categories. Standard weighting may be astandard low weighting or may be a variable score on a scale of possiblescores based on analysis of the user browsing history. Accordingly, theauthority indications gleaned from the browsing behavior of thenon-expert or less-expert user can have a less significant impact on acategorical authority ranking for the content pages than authorityindications gleaned from the browsing behavior of expert users. Asdiscussed above, the expert scores can be generated offline by theweighting module 152 and retrieved during the authority ranking process500.

At decision block 535, the association map building service 150 candetermine whether there are additional unassigned users that contributedto the browsing history. An unassigned user can be a user who has notyet been associated with categories and/or determined to have expert ornon-expert status within the categories.

If there are additional unassigned users that contributed to thebrowsing history, then the process transitions back to block 505 toassign a next user to one or more categories based on an analysis ofthat user's browsing behavior. Accordingly, blocks 505 through 535 arerepeated until all users who have contributed to the browsing historyare assigned a status of expert or not expert.

Once there are no additional unassigned users that contributed to thebrowsing history, then the process transitions back to block 540 tostore weighted implicit and explicit page authority indications incontent to authority indication association mappings, for example foruse in determining categorical authority rankings of pages. Afterstoring the content to authority indication association mappings theprocess 500 ends.

Terminology

Depending on the embodiment, certain acts, events, or functions of anyof the processes or algorithms described herein can be performed in adifferent sequence, can be added, merged, or left out altogether (e.g.,not all described operations or events are necessary for the practice ofthe algorithm). Moreover, in certain embodiments, operations or eventscan be performed concurrently, e.g., through multi-threaded processing,interrupt processing, or multiple processors or processor cores or onother parallel architectures, rather than sequentially.

The various illustrative logical blocks, modules, routines, andalgorithm steps described in connection with the embodiments disclosedherein can be implemented as electronic hardware, computer software, orcombinations of both. To clearly illustrate this interchangeability ofhardware and software, various illustrative components, blocks, modules,and steps have been described above generally in terms of theirfunctionality. Whether such functionality is implemented as hardware orsoftware depends upon the particular application and design constraintsimposed on the overall system. The described functionality can beimplemented in varying ways for each particular application, but suchimplementation decisions should not be interpreted as causing adeparture from the scope of the disclosure.

Moreover, the various illustrative logical blocks and modules describedin connection with the embodiments disclosed herein can be implementedor performed by a machine, such as a general purpose processor device, adigital signal processor (DSP), an application specific integratedcircuit (ASIC), a field programmable gate array (FPGA) or otherprogrammable logic device, discrete gate or transistor logic, discretehardware components, or any combination thereof designed to perform thefunctions described herein. A general purpose processor device can be amicroprocessor, but in the alternative, the processor device can be acontroller, microcontroller, or state machine, combinations of the same,or the like. A processor device can include electrical circuitryconfigured to process computer-executable instructions. In anotherembodiment, a processor device includes an FPGA or other programmabledevice that performs logic operations without processingcomputer-executable instructions. A processor device can also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration. Although described herein primarily with respect todigital technology, a processor device may also include primarily analogcomponents. For example, some or all of the signal processing algorithmsdescribed herein may be implemented in analog circuitry or mixed analogand digital circuitry. A computing environment can include any type ofcomputer system, including, but not limited to, a computer system basedon a microprocessor, a mainframe computer, a digital signal processor, aportable computing device, a device controller, or a computationalengine within an appliance, to name a few.

The elements of a method, process, routine, or algorithm described inconnection with the embodiments disclosed herein can be embodieddirectly in hardware, in a software module executed by a processordevice, or in a combination of the two. A software module can reside inRAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory,registers, hard disk, a removable disk, a CD-ROM, or any other form of anon-transitory computer-readable storage medium. An exemplary storagemedium can be coupled to the processor device such that the processordevice can read information from, and write information to, the storagemedium. In the alternative, the storage medium can be integral to theprocessor device. The processor device and the storage medium can residein an ASIC. The ASIC can reside in a user terminal. In the alternative,the processor device and the storage medium can reside as discretecomponents in a user terminal.

Conditional language used herein, such as, among others, “can,” “could,”“might,” “may,” “e.g.,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without other input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list.

Disjunctive language such as the phrase “at least one of X, Y, Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to present that an item, term, etc., may beeither X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z).Thus, such disjunctive language is not generally intended to, and shouldnot, imply that certain embodiments require at least one of X, at leastone of Y, or at least one of Z to each be present.

While the above detailed description has shown, described, and pointedout novel features as applied to various embodiments, it can beunderstood that various omissions, substitutions, and changes in theform and details of the devices or algorithms illustrated can be madewithout departing from the spirit of the disclosure. As can berecognized, certain embodiments described herein can be embodied withina form that does not provide all of the features and benefits set forthherein, as some features can be used or practiced separately fromothers. The scope of certain embodiments disclosed herein is indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

What is claimed is:
 1. A system for assigning authority rankings tocontent items, the system comprising: a browser component adapted to runon computing devices of a plurality of browser users, the browsercomponent configured to cause storage of browsing history data in amemory, the browsing history data comprising: traffic data indicatingvisits by the plurality of browser users to a plurality of content itemsof a plurality of content sites, and user interactions with content ofat least a subset of the plurality of content items; and an intermediarysystem that communicates over a network with the browser componentadapted to run on the user device, the intermediary system comprisingone or more processors configured to: receive the browsing history datafrom the browser component on the computing devices of a plurality ofbrowser users, generate, based at least partly on analyzing the trafficdata, implicit authority indications for each of the plurality ofcontent items, wherein generating the implicit authority indication fora content item having content on a particular topic comprises (1)generating, for each of a plurality of users that access the contentitem, a respective expertise score for the topic, the expertise scorebased at least partly on how frequently the respective user accessesother content items on said topic as determined from the traffic data;and (2) using an average of the expertise scores of the plurality ofusers to generate an implicit authority score for the content item,generate, based at least partly on the user interactions, explicitauthority indications for at least the subset of the plurality ofcontent items, build an authority association map associating each ofthe plurality of content items with any corresponding implicit authorityindications and explicit authority indications, and assign authorityrankings to specific content items based at least partly on theauthority association map, wherein the authority rankings indicate oneor both of page authority representing relevance of content of thespecific content items to particular topics and domain authorityrepresenting the reliability and relevance of the specific content itemsto the particular topics.
 2. The system of claim 1, wherein the browsercomponent includes a content sharing module configured to provide a userinterface having functionality for the user to share content items onsocial media, the user interactions including sharing of content itemsby the user on social media.
 3. The system of claim 2, the contentsharing module configured to cause storage of data representing usersharing of content on social media with the browsing history data. 4.The system of claim 1, wherein the browser component includes a contentrating module configured to provide a user interface havingfunctionality for the user to provide authority feedback representinguser-perceived authority of content items, the user interactionsincluding user-provided authority feedback.
 5. The system of claim 4,the content rating module configured to cause storage of datarepresenting the authority feedback with the browsing history data. 6.The system of claim 4, wherein the functionality of the user interfacecomprises one of a numerical rating system, binary rating system, andscale rating system for enabling the user to provide the authorityfeedback.
 7. The system of claim 1, wherein the authority rankingsindicate page authority.
 8. The system of claim 1, wherein the authorityrankings indicate domain authority.
 9. The system of claim 1, whereinthe authority rankings indicate both of page authority and domainauthority.
 10. A system for assigning authority rankings to contentitems, the system comprising: a map building service comprising one ormore processors configured to: receive browsing history data fromcomputing devices of a plurality of browser users, the browsing historydata comprising: traffic data indicating visits by the plurality ofbrowser users to a plurality of content items of a plurality of contentsites, and user interactions with content of at least a subset of theplurality of content items, generate, based at least partly on analyzingthe traffic data, implicit authority indications for each of theplurality of content items, wherein generating the implicit authorityindication for a content item having content on a particular topiccomprises (1) generating, for each of a plurality of users that accessthe content item, a respective expertise score for the topic, theexpertise score based at least partly on how frequently the respectiveuser accesses other content items on said topic as determined from thetraffic data; and (2) using an average of the expertise scores of theplurality of users to generate an implicit authority score for thecontent item, generate, based at least partly on the user interactions,explicit authority indications for at least the subset of the pluralityof content items, and build an authority association map associatingeach of the plurality of content items with any corresponding implicitauthority indications and explicit authority indications; and anauthority ranking service comprising one or more processors configuredto assign authority rankings to specific content items based at leastpartly on weighting the implicit and explicit authority indications inthe authority association map, wherein the authority rankings indicateone or both of page authority representing relevance of content of thespecific content items to particular topics and domain authorityrepresenting the reliability and relevance of the specific content itemsto the particular topics.
 11. The system of claim 10, the userinteractions comprising user-provided authority feedback representinguser-perceived authority of at least some of the plurality of contentitems.
 12. The system of claim 10, the user interactions comprisingsocial media sharing by a user of a content item.
 13. The system ofclaim 10, wherein the map building service is further configured toassociate one or more users and one or more content items with acategory.
 14. The system of claim 10, further comprising an authorityutilization module configured provide a service portal for a contentitem of the plurality of content items.
 15. The system of claim 14,wherein the service portal comprises a user interface displaying datarepresenting an authority ranking assigned to the content item.
 16. Thesystem of claim 14, wherein the service portal comprises a userinterface displaying trend data illustrating change in an authorityranking assigned to the content item over time.
 17. The system of claim14, wherein the service portal comprises a user interface displayingtips for improving an authority ranking assigned to the content item.18. The system of claim 10, further comprising an authority utilizationmodule configured to use the authority ranking assigned to a contentitem to dynamically adjust a presentation of the content item for a uservisit to the content item.
 19. A method for assigning authority rankingsto content items, the method comprising, by an intermediary system thatoperates as an intermediary between user devices and content servers:receiving browsing history data from computing devices of a plurality ofbrowser users, the browsing history data comprising: traffic dataindicating visits by the plurality of browser users to a plurality ofcontent items of a plurality of content sites, and user interactionswith content of at least a subset of the plurality of content items,generating, based at least partly on analyzing the traffic data,implicit authority indications for each of the plurality of contentitems, wherein generating the implicit authority indication for acontent item having content on a particular topic comprises (1)generating, for each of a plurality of users that access the contentitem, a respective expertise score for the topic, the expertise scorebased at least partly on how frequently the respective user accessesother content items on said topic as determined from the traffic data;and (2) using an average of the expertise scores of the plurality ofusers to generate an implicit authority score for the content item;generating, based at least partly on the user interactions, explicitauthority indications for at least the subset of the plurality ofcontent items; and building an authority association map associatingeach of the plurality of content items with any corresponding implicitauthority indications and explicit authority indications; and assigningauthority rankings to specific content items based at least partly onweighting the implicit and explicit authority indications in theauthority association map, wherein the authority rankings indicate oneor both of page authority representing relevance of content of thespecific content items to particular topics and domain authorityrepresenting the reliability and relevance of the specific content itemsto the particular topics; wherein the intermediary system comprises oneor more computing devices and is separate from the user device.
 20. Themethod of claim 19, wherein the user interactions comprise one or moreof user-provided authority feedback of a content item of the pluralityof content items, social media sharing of the content item, andbookmarking of the content item.
 21. The method of claim 19, furthercomprising: assigning a user of the plurality of users to at least onecategory based on a portion of the browsing history data associated withthe user; determining one or more content items of the plurality ofcontent items associated with the at least one category; identifying,based at least partly on analyzing the portion of the browsing historydata associated with the user, categorical authority indicationscomprising implicit authority indications and explicit authorityindications associated with the at least one category; including, in theauthority association map, associations between the subset of thecategorical authority indications and the one or more content items; anddetermining whether the user is an expert in the at least one category.22. The method of claim 21, the method further comprising, in responseto determining that the user is an expert in the at least one category,assigning a relatively higher weighting to the categorical authorityindications when ranking the one or more content items.